numpy · charris · Sep 11, 2024 · Sep 4, 2024
diff --git a/.spin/cmds.py b/.spin/cmds.py
@@ -508,7 +508,7 @@ def lint(ctx, branch, uncommitted):
     Examples:
 
     \b
-    For lint checks of your development brach with `main` or a custom branch:
+    For lint checks of your development branch with `main` or a custom branch:
 
     \b
     $ spin lint # defaults to main

diff --git a/benchmarks/benchmarks/bench_io.py b/benchmarks/benchmarks/bench_io.py
@@ -88,7 +88,7 @@ def setup(self, num_lines):
         # unfortunately, timeit will only run setup()
         # between repeat events, but not for iterations
         # within repeats, so the StringIO object
-        # will have to be rewinded in the benchmark proper
+        # will have to be rewound in the benchmark proper
         self.data_comments = StringIO('\n'.join(data))
 
     def time_comment_loadtxt_csv(self, num_lines):

diff --git a/doc/neps/nep-0021-advanced-indexing.rst b/doc/neps/nep-0021-advanced-indexing.rst
@@ -649,7 +649,7 @@ eventualities.
 Copyright
 ---------
 
-This document is placed under the CC0 1.0 Universell (CC0 1.0) Public Domain Dedication [1]_.
+This document is placed under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication [1]_.
 
 
 References and footnotes

diff --git a/doc/neps/nep-0048-spending-project-funds.rst b/doc/neps/nep-0048-spending-project-funds.rst
@@ -125,7 +125,7 @@ a volunteer in a reasonable amount of time.
 There are also many tasks, activities, and projects outside of
 development work that are important and could enhance the project or community
 - think of, for example, user surveys, translations, outreach, dedicated
-mentoring of newcomers, community organizating, website improvements, and
+mentoring of newcomers, community organizing, website improvements, and
 administrative tasks.
 
 Time of people to perform tasks is also not the only thing that funds can be

diff --git a/doc/neps/nep-0053-c-abi-evolution.rst b/doc/neps/nep-0053-c-abi-evolution.rst
@@ -253,7 +253,7 @@ a user to:
   yet compatible.
 
 The import of ``numpy2_compat`` (and an error when it is missing) will be
-inserted by the NumPy eaders as part of the ``import_array()`` call.
+inserted by the NumPy headers as part of the ``import_array()`` call.
 
 Alternatives
 ============

diff --git a/doc/source/f2py/f2py-testing.rst b/doc/source/f2py/f2py-testing.rst
@@ -45,7 +45,7 @@ class present in ``util.py``.
 
 This class many helper functions for parsing and compiling test source files. Its child 
 classes can override its ``sources`` data member to provide their own source files.
-This superclass will then compile the added source files upon object creation andtheir
+This superclass will then compile the added source files upon object creation and their
 functions will be appended to ``self.module`` data member. Thus, the child classes will
 be able to access the fortran functions specified in source file by calling
 ``self.module.[fortran_function_name]``.

diff --git a/doc/source/reference/c-api/array.rst b/doc/source/reference/c-api/array.rst
@@ -2920,7 +2920,7 @@ of this useful approach to looping over an array from C.
 
 .. c:function:: void PyArray_ITER_NEXT(PyObject* iterator)
 
-    Incremement the index and the dataptr members of the *iterator* to
+    Increment the index and the dataptr members of the *iterator* to
     point to the next element of the array. If the array is not
     (C-style) contiguous, also increment the N-dimensional coordinates
     array.

diff --git a/doc/source/reference/c-api/datetimes.rst b/doc/source/reference/c-api/datetimes.rst
@@ -194,7 +194,7 @@ Conversion functions
 
     Returns the string length to use for converting datetime
     objects with the given local time and unit settings to strings.
-    Use this when constructings strings to supply to
+    Use this when constructing strings to supply to
     ``NpyDatetime_MakeISO8601Datetime``.
 
 .. c:function:: int NpyDatetime_MakeISO8601Datetime(\

diff --git a/doc/source/reference/simd/build-options.rst b/doc/source/reference/simd/build-options.rst
@@ -203,7 +203,7 @@ Behaviors
           # is equivalent to
           python -m build --wheel -Csetup-args=-Dcpu-baseline="sse sse2 sse3 ssse3 sse41 popcnt sse42"
 
-- ``cpu-dispatch`` does not combain any of implied CPU features,
+- ``cpu-dispatch`` does not combine any of implied CPU features,
   so you must add them unless you want to disable one or all of them::
 
     # Only dispatches AVX2 and FMA3

diff --git a/doc/source/reference/simd/how-it-works.rst b/doc/source/reference/simd/how-it-works.rst
@@ -201,7 +201,7 @@ through ``--cpu-dispatch``, but it can also represent other options such as:
       #define NPY__CPU_TARGET_AVX2
       #define NPY__CPU_TARGET_AVX512F
       // our dispatch-able source
-      #include "/the/absuolate/path/of/hello.dispatch.c"
+      #include "/the/absolute/path/of/hello.dispatch.c"
 
 - **(D) Dispatch-able configuration header**: The infrastructure
   generates a config header for each dispatch-able source, this header
@@ -234,7 +234,7 @@ through ``--cpu-dispatch``, but it can also represent other options such as:
           // the additional optimizations, so it could be SSE42 or AVX512F
         #define CURRENT_TARGET(X) NPY_CAT(NPY_CAT(X, _), NPY__CPU_TARGET_CURRENT)
       #endif
-      // Macro 'CURRENT_TARGET' adding the current target as suffux to the exported symbols,
+      // Macro 'CURRENT_TARGET' adding the current target as suffix to the exported symbols,
       // to avoid linking duplications, NumPy already has a macro called
       // 'NPY_CPU_DISPATCH_CURFX' similar to it, located at
       // numpy/numpy/_core/src/common/npy_cpu_dispatch.h

diff --git a/doc/source/release/1.10.0-notes.rst b/doc/source/release/1.10.0-notes.rst
@@ -187,7 +187,7 @@ New Features
 Reading extra flags from site.cfg
 ---------------------------------
 Previously customization of compilation of dependency libraries and numpy
-itself was only accomblishable via code changes in the distutils package.
+itself was only accomplishable via code changes in the distutils package.
 Now numpy.distutils reads in the following extra flags from each group of the
 *site.cfg*:
 

diff --git a/doc/source/user/basics.creation.rst b/doc/source/user/basics.creation.rst
@@ -87,7 +87,7 @@ you create the array.
 ===========================================
 
 ..
-  40 functions seems like a small number, but the routies.array-creation
+  40 functions seems like a small number, but the routines.array-creation
   has ~47. I'm sure there are more. 
 
 NumPy has over 40 built-in functions for creating arrays as laid

diff --git a/doc/source/user/c-info.python-as-glue.rst b/doc/source/user/c-info.python-as-glue.rst
@@ -831,7 +831,7 @@ file that defines the interface. Often, however, this ``.i`` file can
 be parts of the header itself. The interface usually needs a bit of
 tweaking to be very useful. This ability to parse C/C++ headers and
 auto-generate the interface still makes SWIG a useful approach to
-adding functionalilty from C/C++ into Python, despite the other
+adding functionality from C/C++ into Python, despite the other
 methods that have emerged that are more targeted to Python. SWIG can
 actually target extensions for several languages, but the typemaps
 usually have to be language-specific. Nonetheless, with modifications

diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi
@@ -958,7 +958,7 @@ class dtype(Generic[_DTypeScalar_co]):
         metadata: dict[str, Any] = ...,
     ) -> dtype[int_ | np.bool]: ...
     # NOTE: `_: type[float]` also accepts `type[float | int | bool]`
-    # NOTE: `float64` inheritcs from `float` at runtime; but this isn't
+    # NOTE: `float64` inherits from `float` at runtime; but this isn't
     # reflected in these stubs. So an explicit `float64` is required here.
     @overload
     def __new__(

diff --git a/numpy/_core/_add_newdocs.py b/numpy/_core/_add_newdocs.py
@@ -5741,7 +5741,7 @@
     >>> np.add.resolve_dtypes((float32, float, None))
     (dtype('float32'), dtype('float32'), dtype('float32'))
 
-    Where the Python ``float`` behaves samilar to a Python value ``0.0``
+    Where the Python ``float`` behaves similar to a Python value ``0.0``
     in a ufunc call.  (See :ref:`NEP 50 <NEP50>` for details.)
 
     """))

diff --git a/numpy/_core/_machar.py b/numpy/_core/_machar.py
@@ -115,7 +115,7 @@ def __init__(self, float_conv=float,int_conv=int,
 
         """
         # We ignore all errors here because we are purposely triggering
-        # underflow to detect the properties of the runninng arch.
+        # underflow to detect the properties of the running arch.
         with errstate(under='ignore'):
             self._do_init(float_conv, int_conv, float_to_float, float_to_str, title)
 

diff --git a/numpy/_core/fromnumeric.py b/numpy/_core/fromnumeric.py
@@ -4027,7 +4027,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue, *,
 
         \sqrt{\frac{\sum_i{|a_i - \bar{a}|^2 }}{N - 1}}
 
-    In statistics, the resulting quantity is sometimed called the "sample
+    In statistics, the resulting quantity is sometimes called the "sample
     standard deviation" because if `a` is a random sample from a larger
     population, this calculation provides the square root of an unbiased
     estimate of the variance of the population. The use of :math:`N-1` in the
@@ -4232,7 +4232,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue, *,
 
         \frac{\sum_i{|a_i - \bar{a}|^2}}{N - 1}
 
-    In statistics, the resulting quantity is sometimed called the "sample
+    In statistics, the resulting quantity is sometimes called the "sample
     variance" because if `a` is a random sample from a larger population,
     this calculation provides an unbiased estimate of the variance of the
     population.  The use of :math:`N-1` in the denominator is often called

diff --git a/numpy/_core/src/common/dlpack/dlpack.h b/numpy/_core/src/common/dlpack/dlpack.h
@@ -109,7 +109,7 @@ typedef enum {
    */
   kDLCUDAManaged = 13,
   /*!
-   * \brief Unified shared memory allocated on a oneAPI non-partititioned
+   * \brief Unified shared memory allocated on a oneAPI non-partitioned
    * device. Call to oneAPI runtime is required to determine the device
    * type, the USM allocation type and the sycl context it is bound to.
    *

diff --git a/numpy/_core/src/common/npy_cpu_features.c b/numpy/_core/src/common/npy_cpu_features.c
@@ -849,7 +849,7 @@ npy__cpu_init_features(void)
 {
     /*
      * just in case if the compiler doesn't respect ANSI
-     * but for knowing platforms it still nessecery, because @npy__cpu_init_features
+     * but for knowing platforms it still necessary, because @npy__cpu_init_features
      * may called multiple of times and we need to clear the disabled features by
      * ENV Var or maybe in the future we can support other methods like
      * global variables, go back to @npy__cpu_try_disable_env for more understanding

diff --git a/numpy/_core/src/common/numpyos.c b/numpy/_core/src/common/numpyos.c
@@ -282,7 +282,7 @@ fix_ascii_format(char* buf, size_t buflen, int decimal)
  *      - format: The printf()-style format to use for the code to use for
  *      converting.
  *      - value: The value to convert
- *      - decimal: if != 0, always has a decimal, and at leasat one digit after
+ *      - decimal: if != 0, always has a decimal, and at least one digit after
  *      the decimal. This has the same effect as passing 'Z' in the original
  *      PyOS_ascii_formatd
  *

diff --git a/numpy/_core/src/multiarray/abstractdtypes.c b/numpy/_core/src/multiarray/abstractdtypes.c
@@ -406,7 +406,7 @@ npy_update_operand_for_scalar(
     else if (NPY_UNLIKELY(casting == NPY_EQUIV_CASTING) &&
              descr->type_num != NPY_OBJECT) {
         /*
-         * increadibly niche, but users could pass equiv casting and we
+         * incredibly niche, but users could pass equiv casting and we
          * actually need to cast.  Let object pass (technically correct) but
          * in all other cases, we don't technically consider equivalent.
          * NOTE(seberg): I don't think we should be beholden to this logic.

diff --git a/numpy/_core/src/multiarray/dtypemeta.h b/numpy/_core/src/multiarray/dtypemeta.h
@@ -80,7 +80,7 @@ typedef struct {
     PyObject *castingimpls;
 
     /*
-     * Storage for `descr->f`, since we may need to allow some customizatoin
+     * Storage for `descr->f`, since we may need to allow some customization
      * here at least in a transition period and we need to set it on every
      * dtype instance for backward compatibility.  (Keep this at end)
      */

diff --git a/numpy/_core/src/npysort/selection.cpp b/numpy/_core/src/npysort/selection.cpp
@@ -258,7 +258,7 @@ unguarded_partition_(type *v, npy_intp *tosort, const type pivot, npy_intp *ll,
 /*
  * select median of median of blocks of 5
  * if used as partition pivot it splits the range into at least 30%/70%
- * allowing linear time worstcase quickselect
+ * allowing linear time worst-case quickselect
  */
 template <typename Tag, bool arg, typename type>
 static npy_intp

diff --git a/numpy/_core/src/umath/fast_loop_macros.h b/numpy/_core/src/umath/fast_loop_macros.h
@@ -315,7 +315,7 @@ abs_ptrdiff(char *a, char *b)
 /*
  * stride is equal to element size and input and destination are equal or
  * don't overlap within one register. The check of the steps against
- * esize also quarantees that steps are >= 0.
+ * esize also guarantees that steps are >= 0.
  */
 #define IS_BLOCKABLE_UNARY(esize, vsize) \
     (steps[0] == (esize) && steps[0] == steps[1] && \

diff --git a/numpy/_core/src/umath/loops_arithm_fp.dispatch.c.src b/numpy/_core/src/umath/loops_arithm_fp.dispatch.c.src
@@ -22,7 +22,7 @@
  *    current one kinda slow and it can be optimized by
  *    at least avoiding the division and keep sqrt.
  *  - Vectorize reductions
- *  - Add support for ASIMD/VCMLA through universal intrinics.
+ *  - Add support for ASIMD/VCMLA through universal intrinsics.
  */
 
 //###############################################################################

diff --git a/numpy/_core/src/umath/scalarmath.c.src b/numpy/_core/src/umath/scalarmath.c.src
@@ -937,7 +937,7 @@ convert_to_@name@(PyObject *value, @type@ *result, npy_bool *may_need_deferring)
     if (PyArray_IsScalar(value, @Name@)) {
         *result = PyArrayScalar_VAL(value, @Name@);
         /*
-         * In principle special, assyemetric, handling could be possible for
+         * In principle special, asymmetric, handling could be possible for
          * explicit subclasses.
          * In practice, we just check the normal deferring logic.
          */

diff --git a/numpy/_core/src/umath/ufunc_object.c b/numpy/_core/src/umath/ufunc_object.c
@@ -3005,7 +3005,7 @@ PyUFunc_Reduceat(PyUFuncObject *ufunc, PyArrayObject *arr, PyArrayObject *ind,
     const char *ufunc_name = ufunc_get_name_cstr(ufunc);
     char *opname = "reduceat";
 
-    /* These parameters comefrom a TLS global */
+    /* These parameters come from a TLS global */
     int buffersize = 0, errormask = 0;
 
     NPY_BEGIN_THREADS_DEF;

diff --git a/numpy/_core/tests/test_arrayprint.py b/numpy/_core/tests/test_arrayprint.py
@@ -144,7 +144,7 @@ def test_self_containing(self):
         first[()] = 0  # resolve circular references for garbage collector
 
     def test_containing_list(self):
-        # printing square brackets directly would be ambiguuous
+        # printing square brackets directly would be ambiguous
         arr1d = np.array([None, None])
         arr1d[0] = [1, 2]
         arr1d[1] = [3]
@@ -1128,7 +1128,7 @@ def test_ctx_mgr(self):
         assert_equal(s, '[0.67]')
 
     def test_ctx_mgr_restores(self):
-        # test that print options are actually restrored
+        # test that print options are actually restored
         opts = np.get_printoptions()
         with np.printoptions(precision=opts['precision'] - 1,
                              linewidth=opts['linewidth'] - 4):

diff --git a/numpy/_core/tests/test_casting_unittests.py b/numpy/_core/tests/test_casting_unittests.py
@@ -776,7 +776,7 @@ def test_structured_field_offsets(self, to_dt, expected_off):
             # completely invalid/impossible cast:
             ("i,i", "i,i,i", None),
         ])
-    def test_structured_view_offsets_paramteric(
+    def test_structured_view_offsets_parametric(
             self, from_dt, to_dt, expected_off):
         # TODO: While this test is fairly thorough, right now, it does not
         # really test some paths that may have nonzero offsets (they don't

diff --git a/numpy/_core/tests/test_dtype.py b/numpy/_core/tests/test_dtype.py
@@ -1526,7 +1526,7 @@ def test_float_int_pyscalar_promote_rational(self, other, expected):
             ])
     def test_permutations_do_not_influence_result(self, dtypes, expected):
         # Tests that most permutations do not influence the result.  In the
-        # above some uint and int combintations promote to a larger integer
+        # above some uint and int combinations promote to a larger integer
         # type, which would then promote to a larger than necessary float.
         for perm in permutations(dtypes):
             assert np.result_type(*perm) == expected

diff --git a/numpy/_core/tests/test_einsum.py b/numpy/_core/tests/test_einsum.py
@@ -1025,7 +1025,7 @@ def test_broadcasting_dot_cases(self):
 
     def test_output_order(self):
         # Ensure output order is respected for optimize cases, the below
-        # conraction should yield a reshaped tensor view
+        # contraction should yield a reshaped tensor view
         # gh-16415
 
         a = np.ones((2, 3, 5), order='F')

diff --git a/numpy/_core/tests/test_indexing.py b/numpy/_core/tests/test_indexing.py
@@ -367,7 +367,7 @@ def test_trivial_fancy_not_possible(self):
         assert_array_equal(a[idx], idx)
 
         # this case must not go into the fast path, note that idx is
-        # a non-contiuguous none 1D array here.
+        # a non-contiguous none 1D array here.
         a[idx] = -1
         res = np.arange(6)
         res[0] = -1

diff --git a/numpy/_core/tests/test_multiarray.py b/numpy/_core/tests/test_multiarray.py
@@ -4767,7 +4767,7 @@ class TestArgmax:
             ([np.nan, 0, 1, 2, 3], 0),
             ([np.nan, 0, np.nan, 2, 3], 0),
             # To hit the tail of SIMD multi-level(x4, x1) inner loops
-            # on variant SIMD widthes
+            # on variant SIMD widths
             ([1] * (2*5-1) + [np.nan], 2*5-1),
             ([1] * (4*5-1) + [np.nan], 4*5-1),
             ([1] * (8*5-1) + [np.nan], 8*5-1),
@@ -4910,7 +4910,7 @@ class TestArgmin:
             ([np.nan, 0, 1, 2, 3], 0),
             ([np.nan, 0, np.nan, 2, 3], 0),
             # To hit the tail of SIMD multi-level(x4, x1) inner loops
-            # on variant SIMD widthes
+            # on variant SIMD widths
             ([1] * (2*5-1) + [np.nan], 2*5-1),
             ([1] * (4*5-1) + [np.nan], 4*5-1),
             ([1] * (8*5-1) + [np.nan], 8*5-1),

diff --git a/numpy/_core/tests/test_scalarmath.py b/numpy/_core/tests/test_scalarmath.py
@@ -1159,7 +1159,7 @@ def test_scalar_matches_array_op_with_pyscalar(op, sctype, other_type, rop):
     assert res == expected
     if isinstance(val1, float) and other_type is complex and rop:
         # Python complex accepts float subclasses, so we don't get a chance
-        # and the result may be a Python complelx (thus, the `np.array()``)
+        # and the result may be a Python complex (thus, the `np.array()``)
         assert np.array(res).dtype == expected.dtype
     else:
         assert res.dtype == expected.dtype
diff --git a/numpy/_typing/_dtype_like.py b/numpy/_typing/_dtype_like.py
@@ -129,7 +129,7 @@ def dtype(self) -> _DType_co: ...
 
 # NOTE: while it is possible to provide the dtype as a dict of
 # dtype-like objects (e.g. `{'field1': ..., 'field2': ..., ...}`),
-# this syntax is officially discourged and
+# this syntax is officially discouraged and
 # therefore not included in the type-union defining `DTypeLike`.
 #
 # See https://github.com/numpy/numpy/issues/16891 for more details.

diff --git a/numpy/distutils/command/config_compiler.py b/numpy/distutils/command/config_compiler.py
@@ -57,7 +57,7 @@ def initialize_options(self):
         self.noarch = None
 
     def finalize_options(self):
-        log.info('unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options')
+        log.info('unifying config_fc, config, build_clib, build_ext, build commands --fcompiler options')
         build_clib = self.get_finalized_command('build_clib')
         build_ext = self.get_finalized_command('build_ext')
         config = self.get_finalized_command('config')
@@ -98,7 +98,7 @@ def initialize_options(self):
         self.compiler = None
 
     def finalize_options(self):
-        log.info('unifing config_cc, config, build_clib, build_ext, build commands --compiler options')
+        log.info('unifying config_cc, config, build_clib, build_ext, build commands --compiler options')
         build_clib = self.get_finalized_command('build_clib')
         build_ext = self.get_finalized_command('build_ext')
         config = self.get_finalized_command('config')

diff --git a/numpy/distutils/exec_command.py b/numpy/distutils/exec_command.py
@@ -306,7 +306,7 @@ def _quote_arg(arg):
     """
     Quote the argument for safe use in a shell command line.
     """
-    # If there is a quote in the string, assume relevants parts of the
+    # If there is a quote in the string, assume relevant parts of the
     # string are already quoted (e.g. '-I"C:\\Program Files\\..."')
     if '"' not in arg and ' ' in arg:
         return '"%s"' % arg

diff --git a/numpy/distutils/mingw32ccompiler.py b/numpy/distutils/mingw32ccompiler.py
@@ -184,7 +184,7 @@ def find_python_dll():
     # - find it in the virtualenv (sys.prefix)
     # - find it in python main dir (sys.base_prefix, if in a virtualenv)
     # - in system32,
-    # - ortherwise (Sxs), I don't know how to get it.
+    # - otherwise (Sxs), I don't know how to get it.
     stems = [sys.prefix]
     if sys.base_prefix != sys.prefix:
         stems.append(sys.base_prefix)

diff --git a/numpy/distutils/tests/test_build_ext.py b/numpy/distutils/tests/test_build_ext.py
@@ -56,7 +56,7 @@ def configuration(parent_package="", top_path=None):
                 from numpy.distutils.core import setup
                 setup(**configuration(top_path="").todict())'''))
 
-    # build the test extensino and "install" into a temporary directory
+    # build the test extension and "install" into a temporary directory
     build_dir = tmp_path
     subprocess.check_call([sys.executable, 'setup.py', 'build', 'install',
                            '--prefix', str(tmp_path / 'installdir'),